40 Resources to Completely Master Markov Decision Processes

The Markov Decision Process is the formal description of the Reinforcement Learning problem. It includes concepts like states, actions, rewards, and how an agent makes decisions based on a given policy. So, what Reinforcement Learning algorithms do is to find optimal solutions to Markov Decision Processes.

Markov Decision Process

Because it is a fundamental concept in the Reinforcement Learning domain, we selected more than 40 resources about Markov Decision Process, including blog posts, books, and videos. Check the links below.